AI-Powered Line Bot with Azure OpenAI

The workflow JSON

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{
  "name": "Line Bot",
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "line-webhook",
        "options": {}
      },
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2.1,
      "position": [
        0,
        0
      ],
      "id": "f17f101c-4f04-4528-8a45-ca16d225a509",
      "name": "Webhook"
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.body.events[0].message.text }}",
        "options": {
          "systemMessage": "\u0e04\u0e38\u0e13\u0e1c\u0e39\u0e49\u0e0a\u0e48\u0e27\u0e22\u0e15\u0e2d\u0e1a\u0e04\u0e33\u0e16\u0e32\u0e21\u0e40\u0e01\u0e35\u0e48\u0e22\u0e27\u0e01\u0e31\u0e1a\u0e01\u0e33\u0e2b\u0e19\u0e14\u0e01\u0e32\u0e23\u0e15\u0e48\u0e32\u0e07 \u0e46 \u0e17\u0e35\u0e48\u0e2d\u0e22\u0e39\u0e48\u0e43\u0e19 event data \u0e16\u0e49\u0e32\u0e1c\u0e39\u0e49\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e16\u0e32\u0e21\u0e40\u0e01\u0e35\u0e48\u0e22\u0e27 event data \u0e43\u0e2b\u0e49\u0e41\u0e2a\u0e14\u0e07\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e02\u0e2d\u0e07 event \u0e19\u0e31\u0e49\u0e19 \u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49 date \u0e0b\u0e36\u0e48\u0e07\u0e40\u0e2b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e15\u0e32\u0e21\u0e01\u0e33\u0e2b\u0e19\u0e14\u0e01\u0e32\u0e23\u0e19\u0e31\u0e49\u0e19\u0e0b\u0e36\u0e48\u0e07\u0e40\u0e01\u0e47\u0e1a\u0e43\u0e19\u0e23\u0e39\u0e1b\u0e41\u0e1a\u0e1a MM/dd/yyyy"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 2.2,
      "position": [
        208,
        0
      ],
      "id": "750e6820-ae02-4891-a37b-f90bf0612212",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "typeVersion": 1,
      "position": [
        144,
        208
      ],
      "id": "81b6c454-5825-408e-aac6-181808eb46e3",
      "name": "Google Gemini Chat Model",
      "credentials": {
        "googlePalmApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "sessionIdType": "customKey",
        "sessionKey": "={{ $json.body.events[0].source.userId }}"
      },
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "typeVersion": 1.3,
      "position": [
        272,
        208
      ],
      "id": "212b21a6-b49c-441c-9f0e-f724c4893b8d",
      "name": "Simple Memory"
    },
    {
      "parameters": {
        "documentId": {
          "__rl": true,
          "value": "1qSYvLmeNfZnUTQSB_hpbK1rnzUvdn_-cnyr3dsv78CM",
          "mode": "list",
          "cachedResultName": "events",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1qSYvLmeNfZnUTQSB_hpbK1rnzUvdn_-cnyr3dsv78CM/edit?usp=drivesdk"
        },
        "sheetName": {
          "__rl": true,
          "value": "gid=0",
          "mode": "list",
          "cachedResultName": "Sheet1",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1qSYvLmeNfZnUTQSB_hpbK1rnzUvdn_-cnyr3dsv78CM/edit#gid=0"
        },
        "options": {}
      },
      "type": "n8n-nodes-base.googleSheetsTool",
      "typeVersion": 4.7,
      "position": [
        416,
        208
      ],
      "id": "31f61c3f-12e5-45f2-9c14-95473795e41c",
      "name": "Event Data",
      "credentials": {
        "googleSheetsOAuth2Api": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://api.line.me/v2/bot/message/reply",
        "sendHeaders": true,
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer zJ4d34kbTLbYYLe+zQgsM1NA2+HXsmrZdO6B+PoqzLFhJksiR50/+bckxpKbOZq/jkWXIoldP5bzRPmGJnr4HDUiL6tjfrWYJpnR7W0blMeb9A9o0nn7OkdPb4+1a3TnfyHQSVLjGjTB9BiLeMOvTgdB04t89/1O/w1cDnyilFU="
            }
          ]
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={\n\"replyToken\":{{ $('Webhook').item.json.body.events[0].replyToken.toJsonString() }},\n\"messages\":[\n{\"type\":\"text\",\n\"text\":{{ $json.output.toJsonString() }}}\n]\n}",
        "options": {}
      },
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        560,
        0
      ],
      "id": "9497f933-951e-4c5d-9ccd-323400fe7ba8",
      "name": "HTTP Request"
    }
  ],
  "connections": {
    "Webhook": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Simple Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Event Data": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "AI Agent": {
      "main": [
        [
          {
            "node": "HTTP Request",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": true,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "cd27ba10-0f3d-4a94-be06-9cb2894f9cf5",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "id": "mvaXswLxz2N0D3QB",
  "tags": []
}

How this works

This workflow enables seamless interaction with LINE messaging by processing incoming messages via a webhook and generating intelligent responses powered by Azure OpenAI, delivering quick and context-aware replies to users on the LINE platform. It's ideal for developers or businesses building chatbots for customer support, notifications, or engagement on LINE, saving time on manual responses and enhancing user experience through AI-driven conversations. The key step involves the AI Agent node, which analyses the message content and crafts a tailored reply using the lmChatAzureOpenAI integration before sending it back via HTTP Request.

Use this workflow when integrating AI into LINE bots for real-time, scalable messaging without custom coding from scratch, particularly for handling queries or automating replies in apps like e-commerce or services. Avoid it for non-messaging tasks or if you lack Azure OpenAI access, as it relies on that for intelligence. Common variations include adding database nodes for conversation history or swapping Azure for other AI providers to fit different setups.

About this workflow

line_bot. Uses lmChatAzureOpenAi, agent, httpRequest. Webhook trigger; 11 nodes.

Source: https://github.com/KuiMing/n8n_agent/blob/4539f71ab276171ae8646a1e35db343a23c7d9e8/n8n/line_bot.json — original creator credit. Request a take-down →

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